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All Journal Jupiter INOVTEK Polbeng - Seri Informatika JITK (Jurnal Ilmu Pengetahuan dan Komputer) INTECOMS: Journal of Information Technology and Computer Science Journal of Applied Engineering and Technological Science (JAETS) JTIK (Jurnal Teknik Informatika Kaputama) Infotech: Jurnal Informatika & Teknologi Jurnal Sistem Informasi Bisnis (JUNSIBI) Jupiter Journal of Computer & Information Technology Ladang Artikel Ilmu Komputer Jurnal Ilmiah Informatika dan Ilmu Komputer Jurnal Informatika dan Rekayasa Perangkat Lunak
Asistyasari, Ayuni
Universitas Bina Sarana Informatika
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Library & Information Science

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Integration of RECA Weighting and MARCOS Methods in Decision Support Systems for the Selection of the Best Customer Recommendations Asistyasari, Ayuni; Arshad, Muhammad Waqas; Chandra, Iryanto; Nuryaman, Yosep; Saputra, Very Hendra
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol. 6 No. 2 (2025): Volume 6 Number 2 June 2025
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jatika.v6i2.219

Abstract

In a competitive business environment, selecting the best customers is a strategic step to improve marketing efficiency and build profitable long-term relationships. However, this process is often constrained by subjectivity in determining criteria and evaluating alternatives. This study aims to develop an objective and measurable decision-making model by integrating of the Respond to Criteria Weighting (RECA weighting) and the method of measurement of alternatives and ranking according to compromise solution (MARCOS). The RECA weighting is used to determine the weight of criteria based on the response to their level of importance, while MARCOS is used to evaluate and rank customer alternatives based on proximity to the ideal solution. The final ranking of customers is determined using the RECA weighting method and MARCOS, which reflects the final value of each customer alternative; Customer 3 obtained the highest final score of 1.2339, indicating the best overall performance based on the established evaluation criteria. Furthermore, Customer 7 and Customer 1 are in second and third place with scores of 1.2096 and 1.1546, respectively, indicating that these three customers are the main candidates to be prioritized in the customer relationship strategy. The result of the integration of these two methods provides a decision support system that is able to generate accurate and logical customer ratings, and supports data-driven strategic decision-making. This model is expected to be an effective solution in improving the quality of business decisions, especially in managing customer relationships more on target and efficiently.
Decision Support System Based on RECA and COPRAS Methods in Performance Evaluation of Non-Permanent Employees Asistyasari, Ayuni; Chandra, Iryanto; Hadad, Sitna Hajar; Nuryaman, Yosep; Wang, Junhai
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol. 6 No. 3 (2025): Volume 6 Number 3 September 2025
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jatika.v6i3.848

Abstract

The evaluation of the performance of non-permanent employees is a significant challenge for organizations due to the high turnover rate and the limited tenure of these employees. The manual evaluation processes often lead to biases, inconsistencies, and a lack of accuracy in supporting decision-making. This research aims to develop a decision support system based on the RECA and COPRAS methods to produce a more objective, transparent, and systematic evaluation. RECA is used to determine the criteria weights proportionally based on each contribution, while COPRAS functions to assess and provide a final ranking of employee performance by considering both benefit and cost-type criteria. The research results show that this system is capable of sorting non-permanent employees fairly with ranking results of E-AS-05 with a score of 100%, E-AS-03 with a score of 97.32%, E-AS-01 with a score of 94.03%, E-AS-02 with a score of 88.34%, and E-AS-04 with a score of 82.19%. The integration of the RECA and COPRAS methods not only enhances the effectiveness of performance evaluation but also provides a tangible contribution to supporting more efficient and sustainable human resource management.
Decision Support System for Choosing the Best Shipping Service for E-Commerce Using the SAW and CRITIC Methods Wang, Junhai; Setiawansyah, Setiawansyah; Rahmanto, Yuri; Asistyasari, Ayuni
Jurnal Ilmiah Informatika dan Ilmu Komputer (JIMA-ILKOM) Vol. 3 No. 2 (2024): Volume 3 Number 2 September 2024
Publisher : PT. SNN MEDIA TECH PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/jima-ilkom.v3i2.32

Abstract

Choosing the best delivery service for e-commerce is a crucial step that can affect customer satisfaction and overall business success. In today's digital era, consumers expect fast, secure, and affordable delivery. The main problem in choosing the best shipping service for e-commerce is often related to several interrelated factors, which can affect the customer experience and business sustainability. One of the biggest challenges is ensuring that products reach customers within the promised time. Delays in delivery can lead to customer dissatisfaction and potentially damage a business's reputation. The combination of SAW and CRITIC methods provides a powerful approach to multi-criteria decision-making. By leveraging the advantages of each method, users can objectively determine the weight of the criteria and evaluate alternatives in a systematic and transparent way. This approach not only improves the accuracy of decisions but also increases decision-makers confidence in the results obtained. Based on the results of the ranking using the method that has been applied, the alternative with the highest score is Pos Indonesia (A6) with a final score of 0.82506, followed by JNE (A1) with a score of 0.76181, and Tiki (A2) with a score of 0.72127. Based on these values, Pos Indonesia ranks first as the best service provider.
OPTIMALISASI MANAJEMEN TRAFIK DAN KEAMANAN DATA PADA JARINGAN INTRANET IBI-K 1957 DENGAN METODE USER BEHAVIOUR ANALYSIS Hidayat, Syamsu; Astried Silvanie; ASISTYASARI, AYUNI; Nuryaman, Yosep
JTIK (Jurnal Teknik Informatika Kaputama) Vol. 7 No. 2 (2023): Volume 7, Nomor 2, Juli 2023
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jtik.v7i2.125

Abstract

The incident of a data breach at one of the national banks as a result of the merger of several Islamic banks in Indonesia for economic reasons has significantly increased concerns about the security of the data of all organizations, including educational organizations such as universities, where there are such as a personal data system and also educational data for the academic community, the open internet sharing systems enabled by universities are highly vulnerable to cyber attacks. For this reason, an optimization measure for the security of the campus network was implemented in this study and, in addition, the Internet connection was made more stable, as it is perceived as very slow at certain hours or during working hours. The use of Mikrotik as a network security tool designed to establish a network security fortress against intruders. In addition to the fact that Mikrotik devices are easy to obtain and inexpensive, and have good security features, the use of the method of analyzing user behavior consists in using a firewall to detect users who download activities with certain criteria are recorded and marked by the firewall , to then restrict access for the user. The. In addition to utilizing Mikrotik's firewall capabilities, the Queue feature is also used with the Simple Queue and Queue Tree methods. In the Simple Queue method, it designates one of the hosts whose bandwidth is limited, while in Queue Tree, it limits the network segments that provide users with maximum bandwidth limits and guarantees bandwidth. Both can be used side by side and work optimally.
Multi-Criteria Decision Model for Ranking the Best Marketplace Using CRISUS Weighting and OPARA Ranking Thalib, Akil; Asistyasari, Ayuni; Nuryaman, Yosep; Oprasto, Raditya Rimbawan; Yudhistira, Aditia
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol. 7 No. 1 (2026): Volume 7 Number 1 March 2026
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jatika.v7i1.1568

Abstract

The rapid growth of e-commerce marketplaces in Indonesia has increased competition among platforms and created challenges in identifying the most suitable marketplace for users and businesses. Previous studies commonly applied conventional Multi-Criteria Decision-Making (MCDM) approaches, yet many of these methods rely heavily on subjective weighting or limited data-based evaluation, which may lead to inconsistent ranking results. Therefore, this study aims to develop a more objective decision-making model for marketplace evaluation by integrating the CRISUS weighting method with the OPARA ranking approach. The dataset consists of quantitative marketplace performance indicators collected from public digital statistics, including monthly visits, annual visits, application ratings, number of downloads, and the number of active sellers for several major marketplaces operating in Indonesia. The CRISUS method is used to determine criterion weights based on actual data variation to reduce subjective bias, while OPARA evaluates the alternatives through an optimized pairwise ratio mechanism to obtain the final preference values. The experimental results indicate that Shopee achieves the highest score of 0.3078, followed by Lazada with 0.2476 and Tokopedia with 0.2327, demonstrating their stronger performance compared with other marketplace alternatives based on the evaluated criteria. These findings contribute both academically and practically by providing a transparent and data-driven MCDM framework that improves the reliability of marketplace ranking and can support stakeholders in making more informed platform selection decisions.
Co-Authors Aditia Yudhistira Akil Thalib Arshad, Muhammad Waqas Astried Silvanie Astried Silvanie Aziz Setyawan Hidayat, Aziz Setyawan Bibit Sudarsono Chandra, Iryanto Felix Wuryo Handono Hidayat, Syamsu Nanang Nuryadi Nuryaman, Yosep Nuryanti Nuryanti Oprasto, Raditya Rimbawan Setiawansyah Setiawansyah Sitna Hajar Hadad Syamsu Hidayat Taufik Baidawi, Taufik Umi Faddilah Umi Faddilah Umi Faddillah Ummi Faddillah Very Hendra Saputra Wang, Junhai Yosep Nuryaman Yuri Rahmanto